Evidence map›Paper›PMID 34778057›Full record

ArticleFrontiers in oncology2021

COVID-19 in Patients With Hematologic Malignancies: A Single Center Retrospective Study.

Xuejun Alice Wang, Adam F Binder, Usama Gergis, Lindsay Wilde

Abstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Xuejun Alice WangDepartment of Internal Medicine, Thomas Jefferson University Hospital, Philadelphia, PA, United States.
Adam F BinderDepartment of Medical Oncology, Division of Hematologic Malignancies, Thomas Jefferson University Hospital, Philadelphia, PA, United States.
Usama GergisDepartment of Medical Oncology, Division of Hematologic Malignancies, Thomas Jefferson University Hospital, Philadelphia, PA, United States.
Lindsay WildeDepartment of Medical Oncology, Division of Hematologic Malignancies, Thomas Jefferson University Hospital, Philadelphia, PA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Initial studies that described the novel coronavirus (COVID-19) reported increased morbidity and mortality in patients with cancer. Of this group, patients with hematologic malignancies (HM) had the highest disease severity and death rates. Subsequent studies have attempted to better describe how COVID-19 affects patients with HM. However, these studies have yielded variable and often contradictory results. We present our single-institution experience with patients with HM who were diagnosed with COVID-19 from March 2020 to March 2021. We report 62 total cases with 10 patients who died during this time. The overall mortality was 16.1%. Mortality during the first two waves of COVID was 27.8% and 25%. Mortality during the third wave of COVID was 10%. The median age of patients was 67 years (range 20-89 years). 55% of patients had lymphoid malignancies and the majority had active disease at the time of diagnosis with COVID-19. 87% of patients had more than one co-morbidity. Important co-morbidities included cardiovascular disease and smoking history. 38.7% of patients had asymptomatic or mild disease, 54.8% required hospitalization, and 17.5% required ICU level care. In patients who required ICU level care, the mortality was 60%.

Indexed as

COVID-19hematologic malignancyleukemialymphomamortalitymultiple myeloma

Identifiers

PMID34778057
PMCPMC8581235

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.